Evidence map›Paper›PMID 32532951›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2020

Clinical Characteristics and Prognosis of 27 Patients with Childhood Acute Megakaryoblastic Leukemia.

Haixiao Qi, Yan Mao, Qian Cao, Xingzhen Sun, Wenxia Kuai, Junhong Song, Li Ma, Ze Hong, Jian Hu, Guoping Zhou

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 37% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Haixiao QiDepartment of Pediatrics, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China (mainland).
Yan MaoDepartment of Pediatrics, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China (mainland).
Qian CaoDepartment of Pediatrics, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China (mainland).
Xingzhen SunDepartment of Pediatrics, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China (mainland).
Wenxia KuaiDepartment of Pediatrics, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China (mainland).
Junhong SongDepartment of Hematology, Shanghai Children's Medical Center Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China (mainland).
Li MaDepartment of Pediatrics, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China (mainland).
Ze HongDepartment of Pediatrics, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China (mainland).
Jian HuDepartment of Pediatrics, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China (mainland).
Guoping ZhouDepartment of Pediatrics, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China (mainland).
Nanjing Medical University · CNHuaian First People’s Hospital · CNJiangsu Province Hospital · CNShanghai Children's Medical Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND The aim of this study was to investigate the clinical features and prognostic factors of childhood acute megakaryoblastic leukemia (AMKL). MATERIAL AND METHODS The data of 27 cases of childhood AMKL admitted from November 2009 to July 2018 were retrospectively analyzed. The survival analysis and prognostic factors were analyzed by Kaplan-Meier method. RESULTS The median follow-up time was 26.4 months in 27 cases, and the complete response rate was 92.31% after 2 chemotherapy courses. Eight patients underwent bone marrow transplantation after 3-6 courses. Five patients died after transplantation, 4 of whom died due to recurrence after transplantation. Of the 27 patients, 10 developed recurrence (37.04%), and 8/10 had recurrence within 1 year. The 3-year overall survival rate and disease-free survival rates were (47±12)% and (36±14)%, respectively. Of the 27 AMKL cases, the 3 with Down syndrome (DS-AMKL) all survived after treatment, and the 3-year overall survival rate was 100%. However, of the other 24 AMKL patients without Down syndrome (non-DS-AMKL), 6 died and 6 abandoned treatment, and the 3-year overall survival rate was only 50%. Univariate analysis showed that 3-year overall survival rate was not correlated to gender, age, number of newly diagnosed white blood cells, karyotype, remission after 2 courses of treatment, and transplant after 3 courses of treatment of childhood AMKL cases. Nevertheless, recurrence and remission after 2 courses of treatment were significantly correlated with 3-year overall survival rate. CONCLUSIONS Children with non-DS-AMKL have a high degree of malignancy and are prone to early recurrence with a poor prognosis, whereas the prognosis of DS-AMKL is relatively good. Recurrence after treatment and remission after 2 courses of treatment are important factors influencing the prognosis of childhood AMKL. Recurrence after transplantation is the leading cause of death in transplantation patients.

Indexed as

Bone Marrow TransplantationAnemiaAntineoplastic Combined Chemotherapy ProtocolsChild, PreschoolDown SyndromeFemaleFeverHemorrhageHepatomegalyHumansInfantKaplan-Meier EstimateKaryotypeLeukemia, Megakaryoblastic, AcuteMaleNeoplasm Recurrence, Local

Identifiers

PMID32532951
PMCPMC7309653
OpenAlexW3034435738

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.